Author: Arif, Muhammad; Zhang, Cheng; Li, Xiangyu; Güngör, Cem; Çakmak, Buğra; Arslantürk, Metin; Tebani, Abdellah; Özcan, Berkay; Subaş, Oğuzhan; Zhou, Wenyu; Piening, Brian; Turkez, Hasan; Fagerberg, Linn; Price, Nathan; Hood, Leroy; Snyder, Michael; Nielsen, Jens; Uhlen, Mathias; Mardinoglu, Adil
Title: iNetModels 2.0: an interactive visualization and database of multi-omics data Cord-id: xjycfh3w Document date: 2021_1_14
ID: xjycfh3w
Snippet: It is essential to reveal the associations between different omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric pa
Document: It is essential to reveal the associations between different omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics and metabolomics as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their own data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and diseases research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.
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